Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.5/7838
Título: Acacia saligna (Labill.) H. Wendl in the Sesimbra county: invaded habitats and potential distribution modeling
Autor: Gutierres, F.
Gil, A.
Reis, E.
Lobo, A.
Neto, C.
Calado, H.
Costa, José Carlos
Palavras-chave: acacia saligna
species distribution model
Data: 2011
Editora: JCR
Citação: Gutierres, F.; Gil, A.; Reis, E.; Lobo, A.; Neto, C; Calado, H. and Costa, J.C. 2011. Acacia saligna (Labill.) H. Wendl in the Sesimbra Council: Invaded habitats and potential distribution modeling. Journal of Coastal Research, SI 64 (Proceedings of the 11th International Coastal Symposium), pg – pg. Szczecin, Poland, ISSN 0749-0208
Resumo: The aim of this study is to establish the spatial pattern of colonization and spread of Acacia saligna by predictive modeling, susceptibility evaluation and to perform a cost-effective analysis in two sites of community importance (Fernão Ferro/Lagoa de Albufeira and Arrábida/Espichel) in the Sesimbra County. The main goal is to increase the knowledge on the invasive process and the potential distribution of the Acacia saligna in Sesimbra County, namely in the Natura 2000 sites. The Artificial Neural Networks model was developed in Open Modeller to predict the potential of occurrence of A. saligna, and is assumed to be conditioned by a set of limiting factors that may be known or modeled. The base information includes a dependent variable (present distribution of specie) and several variables considered as conditioning factors (topographic variables, land use, soils characteristics, river and road distance), organized in a Geographical Information System (GIS) database. This is used to perform spatial analysis, which is focused on the relationships between the presence or absence of the specie and the values of the conditioning factors. The results show a high correspondence between higher values of potential of occurrence and soils characteristics and distance to rivers; these factors seem to benefit the specie’ invasion process. According to the conservation value of each cartographic unit, related to natural habitats included in Habitats Directive (92/43/EEC), the coastal habitats (2130, 2250 and 2230) were the most susceptible to invasion by A. saligna. The predicted A. saligna distribution allows for a more efficient concentration and application of resources (human and financial) in the most susceptible areas to invasion, such as the local and national Protected Areas and the Sites of Community Importance, and is useful to test hypotheses about the specie range characteristics, habitats preferences and habitat partitioning.
Peer review: yes
URI: http://hdl.handle.net/10400.5/7838
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